In Table REF  we list the winners from the AR challenge for years 2019 and 2020 ranked by their performance. More details of these methods are available in the technical reports [1]}, [2]}. We denote SLS for each method based on the technical reports submitted. The table shows that: methods vary in pre-training, with some utilising the weights from the private dataset IG-Kinetics [3]}. Methods that employed spatio-temporal labels (TL=4) as opposed to temporal labels solely, consistently outperform others, highlighting the nature of this dataset: actions take place in the messy environment of participants' kitchens and identifying where the action takes place is consistently helpful. Finally, no work has attempted few-show or efficient learning on the dataset to-date. SLS-TD in this table is thus consistent for all methods.
